This repository contains a data analysis and machine learning project focusing on credit card fraud detection. The project utilizes Google Colab for implementation, data exploration, and model development.
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Data Exploration: Explore the dataset from the UCI Machine Learning Repository to understand its characteristics, distribution, and potential features.
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Algorithm Implementation: Implement basic regression and classification algorithms to build models for detecting credit card fraud.
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Results Representation: Visualize outcomes and insights through plots and graphs to illustrate key findings and performance metrics.
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Technical Report: Read the comprehensive technical report in the
reports/directory for detailed methodology, algorithm choices, parameter tuning, and overall project approach.
- Google Colab
- Python (NumPy, Pandas, Scikit-learn)
- Matplotlib, Seaborn for data visualization